Abhiroop Bhattacharjee

51 papers A* 3A 7C 2Misc 2Journal 35Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Exploration of Algorithm-Hardware Co-Design for Floating-Point Digital Compute-in-Memory. IEEE Comput. Archit. Lett. Xiaochen Peng, Haruki Mori, Abhiroop Bhattacharjee, Brian Crafton, Hidehiro Fujiwara, Kerem Akarvardar
2026	J	`jnl`	Ultrafast Generative AI by Ultradense 3D Integration: A Case Study on LLM-based Edge Inference. ACM Trans. Design Autom. Electr. Syst. Kerem Akarvardar, Xiaoyu Sun, Brian Crafton, Xiaochen Peng, Haruki Mori, Abhiroop Bhattacharjee, Hidehiro Fujiwara, H.-S. Philip Wong
2025	J	`jnl`	ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2025	J	`jnl`	DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration. CoRR Arkapravo Ghosh, Abhishek Moitra, Abhiroop Bhattacharjee, Ruokai Yin, Priyadarshini Panda
2025	C	`conf`	Low-power Spike-based Wearable Analytics on RRAM Crossbars. ISCAS Abhiroop Bhattacharjee, Jinquan Shi, Wei-Chen Chen, Xinxin Wang, Priyadarshini Panda
2025	J	`jnl`	Low-power Spike-based Wearable Analytics on RRAM Crossbars. CoRR Abhiroop Bhattacharjee, Jinquan Shi, Wei-Chen Chen, Xinxin Wang, Priyadarshini Panda
2025	A	`conf`	SITRA: Exploiting Temporal Silence in Spiking Transformers for Fast & Energy-efficient Inference. ISLPED Abhiroop Bhattacharjee, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda
2025	J	`jnl`	TReX- Reusing Vision Transformer's Attention for Efficient Xbar-Based Computing. IEEE Trans. Emerg. Top. Comput. Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2024	Misc	`conf`	Are SNNs Truly Energy-efficient? - A Hardware Perspective. ICASSP Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda
2024	J	`jnl`	ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation. CoRR Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2024	A	`conf`	HaLo-FL: Hardware-Aware Low-Precision Federated Learning. DATE Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2024	J	`jnl`	MCAIMem: A Mixed SRAM and eDRAM Cell for Area and Energy-Efficient On-Chip AI Memory. IEEE Trans. Very Large Scale Integr. Syst. Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2024	A*	`conf`	PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference. DAC Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda
2024	J	`jnl`	PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference. CoRR Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda
2024	J	`jnl`	RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems. IEEE Trans. Emerg. Top. Comput. Intell. Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2024	J	`jnl`	TReX- Reusing Vision Transformer's Attention for Efficient Xbar-based Computing. CoRR Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2024	J	`jnl`	When In-memory Computing Meets Spiking Neural Networks - A Perspective on Device-Circuit-System-and-Algorithm Co-design. CoRR Abhishek Moitra, Abhiroop Bhattacharjee, Yuhang Li, Youngeun Kim, Priyadarshini Panda
2023	J	`jnl`	Are SNNs Truly Energy-efficient? - A Hardware Perspective. CoRR Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda
2023	A	`conf`	DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks. DATE Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2023	J	`jnl`	DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks. CoRR Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2023	—	`conf`	Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing. ACM Great Lakes Symposium on VLSI Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda
2023	J	`jnl`	Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing. CoRR Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda
2023	J	`jnl`	HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms. CoRR Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2023	J	`jnl`	HyDe: A brid PCM/FeFET/SRAM vice-Search for Optimizing Area and Energy-Efficiencies in Analog IMC Platforms. IEEE J. Emerg. Sel. Topics Circuits Syst. Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2023	J	`jnl`	MCAIMem: a Mixed SRAM and eDRAM Cell for Area and Energy-efficient on-chip AI Memory. CoRR Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2023	J	`jnl`	RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems. CoRR Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2023	J	`jnl`	SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2023	J	`jnl`	SpikeSim: An End-to-End Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang, Gokul Krishnan, Yu Cao, Priyadarshini Panda
2023	A*	`conf`	XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing. DAC Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2023	J	`jnl`	XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing. CoRR Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2023	J	`jnl`	XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars. CoRR Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2022	A	`conf`	Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks. DATE Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda
2022	J	`jnl`	Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks. CoRR Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda
2022	A	`conf`	Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars. ISLPED Abhiroop Bhattacharjee, Youngeun Kim, Abhishek Moitra, Priyadarshini Panda
2022	J	`jnl`	Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars. CoRR Abhiroop Bhattacharjee, Youngeun Kim, Abhishek Moitra, Priyadarshini Panda
2022	J	`jnl`	MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning. CoRR Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda
2022	A*	`conf`	MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning. DAC Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda
2022	J	`jnl`	NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Abhiroop Bhattacharjee, Lakshya Bhatnagar, Youngeun Kim, Priyadarshini Panda
2022	Misc	`conf`	Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? ICASSP Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda
2022	J	`jnl`	Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks? CoRR Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda
2022	J	`jnl`	SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. CoRR Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda
2022	J	`jnl`	SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks. CoRR Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang, Gokul Krishnan, Yu Cao, Priyadarshini Panda
2021	A	`conf`	Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks. DATE Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2021	J	`jnl`	Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks. CoRR Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2021	—	`conf`	END-TRUE: Emerging Nanotechnology-Based Double-Throughput True Random Number Generator. VLSI-SoC (Selected Papers) Shubham Rai, Nishant Gupta, Abhiroop Bhattacharjee, Ansh Rupani, Michael Raitza, Jens Trommer, Thomas Mikolajick, Akash Kumar
2021	A	`conf`	Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks. DATE Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2021	J	`jnl`	Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks. CoRR Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2021	C	`conf`	Metastability with Emerging Reconfigurable Transistors: Exploiting Ambipolarity for Throughput. VLSI-SoC Abhiroop Bhattacharjee, Shubham Rai, Ansh Rupani, Michael Raitza, Akash Kumar
2020	J	`jnl`	NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars. CoRR Abhiroop Bhattacharjee, Lakshya Bhatnagar, Youngeun Kim, Priyadarshini Panda
2020	J	`jnl`	Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks. CoRR Abhiroop Bhattacharjee, Priyadarshini Panda
2020	J	`jnl`	SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars. CoRR Abhiroop Bhattacharjee, Priyadarshini Panda

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.